Version 1

We are happy to release version 1 of MDAnalysis!

MDAnalysis 1.x is a stable legacy platform that supports

  • Python 2.7 (on Linux and MacOS only),
  • Python 3.5, 3.6, 3.7 and 3.8 (on Windows (32- and 64-bit), MacOS, and Linux).

The API will not change for any upcoming 1.x versions. This release completes the first phase of our roadmap. From here on, we will focus on developing version 2 of MDAnalysis, which will support Python 3.6+ only, and will include major API changes and improvements.

The 1.0.0, 1.0.1 and 1.1.1 versions of MDAnalysis are the product of more than 18 months effort. They contain a multitude of fixes, deprecations, and new features. We highlight important changes below, but users are strongly encouraged to read the CHANGELOG for full details. All users are recommended to upgrade to 1.1.1, as it includes important fixes.

Upgrading to MDAnalysis version 1.1.1

In Dependencies we list the required dependencies of MDAnaysis version 1; when installing with pip or conda, the correct dependencies should be automatically pulled in by the package manager:

To install with conda from the conda-forge channel run

conda update -c conda-forge mdanalysis

(Note that for Python 2.7 and 3.5, no conda packages are currently available due to the difficulty of building packages for legacy Python versions. Please install with pip.)

To install from PyPi with pip run

pip install --upgrade MDAnalysis

(This will likely build the package from source so you need the appropriate compilers. )

For more help with installation see the Installation instructions in the User Guide.

Notable new additions

We now support several new formats:

We have also added converters to and from other popular analysis packages. We plan to expand in this exciting direction in future versions, as laid out in our interoperability roadmap. For now, we support:

New additions to analysis include:

  • frames and times attributes to AnalysisBase to capture the frames and times that the analysis was run() on. This is accessible to all analyses that subclass AnalysisBase.
  • a correlations module for computing the discrete autocorrelation function
  • a new HydrogenBondAnalysis class for improved and more efficient analysis of hydrogen bonds, which replaces the now deprecated hbond_analysis code
  • an AverageStructure class for computing the average structure of a trajectory out of memory
  • a hole2 module for improved interfacing with the HOLE2 program, which replaces the now deprecated hole module
  • a DensityAnalysis class for improved density analysis, replacing the now deprecated density_from_Universe() code
  • a method to compute the root-mean-square-inner-product of subspaces
  • a method to calculate the cumulative overlap of a vector in a subspace

Other additions to core functionality include:

Miscellaneous performance improvements include:

  • Dihedral selection in the Ramachandran class has been sped up ~700x.
  • TPR parsing has been sped up 2–30x.

Notable improvements

We have improved the flexibility to our atom selection language, allowing for advanced pattern matching operators.

For example, we now support ? for single character matching, so using resname T?R in a selection string for a protein would yield both residues THR and TYR. More information can be found in our selection documentation.

Notable changes to analysis include:

  • The argument order to AnalysisFromFunction are now as specified in the documentation
  • The select keyword has been standardized by removing selection, atomselection, and ref_select in the contact, gnm, helanal, hole, encore, and hydrogenbonds modules
  • The save() functions have been removed from contacts, diffusionmap, hole, lineardensity, and rms modules
  • Progress bars have been replaced with an improved version from tqdm
  • The radius_cut_q method has been added to contacts.Contacts

Other notable improvements to the core functionality include:

  • AtomGroup.guess_bonds now uses periodic boundary information when available
  • The TPRParser now supports GROMACS 2020
  • When reading PDB and XYZ files, MDAnalysis now adds an elements attribute if the provided elements are valid

Important fixes

For the full list of fixed please see the CHANGELOG. The following are selection of fixes that could have either lead to wrong results or were often reported by users as problematic:


  • Neighbor searching, which is a fundamental component of many analyses in MDAnalysis (such as hydrogenbonds and RDF calculation) had a number of bugs in 1.0.0 that could lead to wrong results, in particular with triclinic unit cells. The buggy code was disabled in 1.0.1 and fixed in 1.1.1. See issues #2229, #2345, #2919, #2670, #2930 for details.
  • Fixed a SegmentationFault for the selection “around 0.0 SELECTION” (Issue #2656)
  • now works correctly for compounds and unwrapping (Issue #2984)
  • When bonds are guessed from distances (AtomGroup.guess_bonds), periodic boundary information is properly taken into account. Bonds that were split across the periodic boundary would have not beend correctly guessed previously. (Issue #2350)
  • The testsuite does not fail anymore with newer version of matplotlib (Issue #2191)

File formats

  • PDB files
    • Better handling of cryo-electron microscopy box dimensions in PDB files:
      • When a PDB file is read, a cryo-em 1 Å3 default CRYST1 record will be interpreted as “no dimensions” and the box dimension in MDAnalysis is set to None (Issue #2599)
      • When box dimensions are missing (u.dimensions is None or np.zeros(6)) then a unitary CRYST1 record (cubic box with sides of 1 Å) is written (Issue #2679)
    • PDB files no longer lose chainIDs when reading files without segIDs (Issue #2389)
    • PDBWriter now uses last character of segid as ChainID (Issue #2224)
  • In GRO files, unit cells with box vectors larger than 1000 nm are now correctly handled (Issue #2371)
  • Reading of XTC and TRR files will not anymore fail with an IOError when the hidden offset files cannot be read; instead, the offsets are recalculated from the trajectory (Issue #1893)
  • Masses and charges in HooMD XML files are now correctly read (#2888)


  • PCA analysis:
    • PCA(align=True) now correctly aligns the trajectory and computes the correct means and covariance matrix (Issue #2561)
    • Specifying n_components now correctly selects the PCA components (Issue #2623)
  • Contact Analysis class respects PBC (Issue #2368)


This release brings several deprecations as the package heads towards version 2.0.0.

The following parts of the analysis code will be removed/changed in version 2.0.0:

  • analysis.hole is deprecated in favor of analysis.hole2.
  • analysis.hbonds.HydrogenBondsAnalysis is deprecated in favor of analysis.hydrogenbonds.hbond_analysis.
  • analysis.density.density_from_Universe() is deprecated in favor of analysis.density.DensityAnalysis.
  • The notwithin_coordinates_factory() and density_from_PDB() methods of analysis.density are deprecated.
  • analysis.waterdynamics.HydrogenBondLifetimes is deprecated in favor of analysis.hydrogenbonds.hbond_analysis.HydrogenBondAnalysis.lifetime() (to be implemented in version 2.0.0)
  • analysis.leaflets.LeafletFinder() will no longer accept a filename, in 2.0.0 only Universes will be supported as inputs.
  • analysis.helanal is deprecated and will be replaced by analysis.helix_analysis in 2.0.0.
  • analysis.hbonds.WaterBridgeAnalysis will be moved to analysis.hydrogenbonds.WaterBridgeAnalysis.

The following parts of the readers/writers will be removed/changed in version 2.0.0:

  • Writer.write_next_timestep() is deprecated in favor of Writer.write().
  • Passing Timestep objects to Writer.write() is deprecated. In 2.0.0 only Universe or AtomGroup objects will be accepted.
  • The way in which the NCDFWriter handles scale factors will change in version 2.x (see Issue #2327 for more details).
  • When writing PDB files, MDAnalysis will no longer be using the last letter of the SegID to set the chainID in version 2.0.0.
  • The bfactors and tempfactors attributes (set by the PDB and MMTF parsers respectively), will be aliased in version 2.0.0.
  • When parsing TPR files, resids will be indexed from 1 rather than the current default of 0.

The following part of the core and library components will be removed/changed in version 2.0.0:

  • lib.log.echo() is deprecated in favor of the new lib.log.ProgressBar.
  • core.universe.as_Universe() is deprecated.


We list below the core dependencies and versions that MDAnalysis has been tested on. They are provided as a string for easy use with conda or pip:

  • Python 2.7: biopython==1.76 cython==0.29.15 griddataformats==0.5.0 gsd==1.7.0 matplotlib==2.2.5 mmtf-python==1.1.2 netcdf4==1.3.1 numpy==1.16.5 scipy==1.2.1 tqdm==4.60.0
  • Python 3.5: biopython==1.72 cython==0.28.5 griddataformats==0.5.0 gsd==1.5.3 matplotlib==3.0.0 mmtf-python==1.1.2 netcdf4==1.3.1 numpy==1.15.2 scipy==1.1.0 tqdm==4.60.0
  • Python 3.6: biopython==1.78 cython==0.29.23 griddataformats==0.5.0 gsd==2.1.2 matplotlib==3.3.2 mmtf-python==1.1.2 netcdf4==1.5.4 numpy==1.16.0 scipy==1.5.1 tqdm==4.60.0
  • Python 3.7: biopython==1.78 cython==0.29.23 griddataformats==0.5.0 gsd==2.4.2 matplotlib==3.4.1 mmtf-python==1.1.2 netcdf4==1.5.6 numpy==1.20.2 scipy==1.6.3 tqdm==4.60.0
  • Python 3.8: biopython==1.78 cython==0.29.23 griddataformats==0.5.0 gsd==2.4.2 matplotlib==3.4.1 mmtf-python==1.1.2 netcdf4==1.5.6 numpy==1.20.2 scipy==1.6.3 tqdm==4.60.0

Author statistics

Altogether this represents the work of 42 contributors from around the world, and featured the work of 25 new contributors:

The MDAnalysis Project gratefully acknowledges a Small Development Grant provided by NumFOCUS.

— The MDAnalysis Team

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MDAnalysis Workshop @ PRACE / SURF

MDAnalysis will be delivering a 3 half-day remote (online) workshop hosted by PRACE / SURF on the 26-28th of May 2021.

The workshop will include both lecture and practical portions. We will cover topics including:

  • The fundamentals and basics of MDAnalysis
  • How to use existing analyses
  • How to write your own analyses
  • Parallel analysis in an HPC setting (using SURFsara supercomputing facilities)
  • Advanced functionality such as universe construction and transformations

The workshop is aimed at users in academia and industry who are already familiar with Python and molecular dynamics. We will have separate sessions at different levels, ranging from introductory to advanced use. MDAnalysis developers will be present to help you during practical portions of the sessions and to answer your questions about how to work productively with MDAnalysis. We will also be holding office hours for extended tutoring – ask us for help with the design of your own workflows!

Register soon (places limited)

The workshop is open to everyone, but places are limited. Apply early!

For more information and the registration form, please see the workshop overview website.